Introduction
For our fourth year at Polytech Sorbonne, we have developed an embedded monitoring system that measures various low-power connected sensors. We used various sensors that transmitted data to the cloud via the LoraWAN antenna (The Things Network).
Our issue addresses the potential transmission of viruses in public spaces and the importance of refreshing the air in these spaces to limit the spread of the virus. To achieve this, it is suggested to measure the level of CO2 in closed spaces as it is correlated with the presence of people and can indicate when it is time to ventilate.
The project aims to develop a connected system equipped with sensors to measure several parameters such as the presence of people in the room, the noise level, temperature, humidity, and CO2 level. These data will then be transmitted to a server using a long-range and low-power consumption technology. The alert thresholds can be calibrated, and the system parameters can be adjusted through a web application.
The measured data will be accessible in graphical form via a web interface on a computer. The system will also send alerts when abnormal behavior is detected. This project will, therefore, enable real-time monitoring of the comfort level of the rooms and ensure health safety in public spaces.
General Schematic
The administrator accesses the Ubidots dashboard to view all sensor data. In case of a spike in CO2 concentration in a room equipped with the monitoring system, the administrator is alerted via the website.
On this dashboard, the administrator can remotely read the following data: temperature, CO2 level, humidity level, pressure sensor, etc.
This dashboard is updated every 10 minutes, which is a relatively long time, but it allows the system to limit its power consumption and thus make it self-sustainable through the use of solar panels.
Red LED flash during 7 seconds when the limit of 1000 PPM is exceeded.
Measuring data and sending it
Using 4 sensors:
T° et d'humidité DHT11
The DHT11 is a capacitive humidity sensor and a thermistor used to measure ambient air and generate a digital signal on the data pin. It is fairly easy to use and inexpensive. The only real drawback of this sensor is that new data can only be obtained once every 2 seconds.
Power Supply: 3 to 5 V
Connectors: 4 pins
Dimensions: 15.5mm x 12mm x 5.5mm
Air quality sensor CCS811 SEN0339
The CCS 811 is a low-power CO2 sensor that integrates a metal oxide (MOX) gas sensor to detect a wide range of volatile organic compounds (VOCs) for indoor air quality monitoring.
Power Supply: 1.8 or 3.6 VDC
Connectors: 10-pin LGA
Dimensions: 2.7 x 4.0 x 1.1 mm
Atmospheric pressure BMP388 SEN0371
This barometric sensor is based on a BMP 388 circuit that allows for atmospheric pressure measurement. The BMP 388 circuit offers low power consumption, higher resolution, and better sampling rate compared to other sensors in the BMP series.
Power Supply: 3.3 to 5 VDC
Connectors: Male connectors
Dimensions: 18 x 11.5 mm
Fermion SEN0487 Micro MEMS Module
This sound sensor based on an omnidirectional MEMS microphone delivers an analog voltage based on the sound level.
Power Supply: 3.3 to 5 VDC
Connectors: Male connectors
Dimensions: 18 x 12.5 mm
MKR WAN 1310 card to interface sensors and send data via the Lora network
The Arduino MKR WAN 1310 board is equipped with a SAMD21 processor (Cortex M0+) and a LoRa interface, making it a very interesting board for IoT projects due to its low power consumption and LoRa connectivity.
The LoRa protocol is a low-rate wireless network that uses a frequency of 868 MHz, allowing for extended range for connected objects in a large part of France. Moreover, the configuration of this protocol is simple and energy-efficient.
The MKR WAN 1310 version includes a 3.7 VDC LiPo/Li-Ion battery charger with a JST connector and an SPI Flash memory in addition to the previous version, the MKR WAN 1300. The board can be programmed via its micro-USB port.
We utilized an Arduino MKR 1310 microcontroller and several libraries, including MKRWAN, Arduino Low Power, Adafruit EPD, etc to gather data from the CO2 sensor. Daytime updates are shown on the screen, and after collecting enough data, it is sent via LoRaWan for efficient and accurate data collection.
Our system is autonomous (Low Power Consumption):
The system is self-sufficient, this posible by using components and limiting the system's consumption.
Components used include:
- 3.7 VDC 1000 mAh LiPo rechargeable battery (L903759)
- 4 solar panels
- Timer to cut off the circuit and limit consumption. We utilized a TPL5110 timer module to conserve energy. This enabled us to activate the CO2 sensor only once every 10 minutes, which significantly decreased power usage and boosted battery longevity. As a result, it is well-suited for extended data collection without the necessity of recharging the LiPo battery. Additionally, we incorporated two indoor solar panels that greatly powering the device during daytime operation.
- Use of low-power consumption sensors
- Switch to turn off the system during holidays for example
Presentation of results :
We have decided to present our results on a user-friendly and intuitive website. In fact, that's why we have chosen to do it on Ubidots.
Comments